Noise reduction method and system for touch detection device

ABSTRACT

Noise reduction method and system for a touch detection device are disclosed. The noise reduction method includes: step A, performing a synchronous sampling on the touch detection nodes in one same group and storing the sampling data; step B, comparing each sampling data against a corresponding reference data to calculate a differential data which, as a detection data, replaces a corresponding original sampling data; step C, calculating statistics of the replacing detection data to screen out valid data to calculate a DC offset component indicative of a noise ingredient; and step D, obtaining noise-filtered detection data by subtracting the DC offset component from each detection data.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a divisional application of U.S. patent applicationSer. No. 13/111,967, filed on May 20, 2011. This application isincorporated herein by reference.

TECHNICAL FIELD

The present invention relates to touch detection technology and, moreparticularly, to a method and system for reducing noise in detectiondata in a touch detection device.

BACKGROUND

Touch detection devices may come in various forms, such as, in the formof a touch key, a touch pad, or a touch screen, and may be classifiedinto various types including infrared (IR) type, resistive type,ultrasonic type, induction type, and capacitive type, in terms of touchdetection manner. As shown in FIG. 1, in one typical touch detectiondevice, a touch controller is connected to a touch sensor to collect andprocess touch detection data of the touch sensor so as to determine acoordinate of a touch point.

Sampling for touch detection data is usually performed on the detectionnodes on a touch sensor in a scanning manner. For example, for acapacitive multipoint touch screen, the detection nodes are a pluralityof projected capacitor nodes arranged in a matrix over a surface of thetouch screen. For a group of touch keys, the detection nodes arerespective sensors positioned in correspondence with the touch keys. Thetouch controller can obtain a matrix of desired sampling data withineach detecting and sampling period by obtaining the sampling data bygroups or individually. FIG. 2 illustrates a sampling data matrixobtained in a touch detection device with M*N nodes in one samplingperiod. In practice, most touch detection devices satisfy the conditionof N+M≥3 except for the situation where a single touch key is used. Dueto limited hardware resources and processing capability of the touchcontroller, to obtain this M*N sampling data matrix, scanning operationsusually need to be performed by groups to achieve a sufficient refreshrate. The nodes may be grouped such that each group includes one or morerows of nodes, one or more columns of nodes, or nodes within arespective preset area. A typical example of such group sampling isarranged row by row, which results in the detection data as follows:

the first row: S₁₁, S₁₂, S₁₃ . . . S_(1j) . . . S_(1n)

the second row: S₂₁, S₂₂, S₂₃ . . . S_(2j) . . . S_(1n)

the i-th row: S_(i1), S_(i2), S_(i3) . . . S_(ij) . . . S_(in)

the m-th row: S_(m1), S_(m2), S_(m3) . . . S_(ij) . . . S_(mn)

According to the basic principle of touch detection, by detecting anddata sampling when no touch event occurs, the touch detection deviceobtains a reference data matrix shown in FIG. 3 and stores the referencedata matrix in a memory. New sampling data is then compared against thereference data to calculate the difference between the new sampling dataand the reference data, as shown in FIG. 4A and FIG. 4B.D _(ij) =S _(ij) −R _(ij)(where i=1,2, . . . m;j=1,2, . . . n)

Therefore, the sampling data sampled in each sampling period can be usedto calculate a corresponding differential data matrix as the touchdetection data for further processing, i.e. for determining whether atouch event occurred or calculating a coordinate or trajectory of atouch point. Exemplary calculating methods include threshold method,watershed method, center-of-gravity method, or the like. Whichevermethod is used, the detection data matrix is compared against apredetermined threshold value or threshold function to thereby determinewhether a touch event occurred and whether the detected coordinate ofthe touch point is valid.

As can be seen from the above description, the reliability, stabilityand resolution of the touch detection results are dependent upon theprecision and stability of the touch detection data. If the samplingvalue S_(ij) includes a noise or error, this noise or error will bepropagated to the differential value D_(ij), such that latercalculations will produce an imprecise result.

However, all touch detection devices are subject to interferences duringpractical use, regardless of the form and detection manner of the touchdetection devices. In many cases, the interferences introduce a largeerror into the touch detection data, which may degrade the stability andresolution of the touch detection result, or even worse, cause the touchdetection device to produce a detection result of false touch or touchfailure.

Take the currently popular capacitive touch screen as an example, inorder to diminish the influence of LCD module and other outsideinterference signals, touch sensors with a double-layered orthree-layered structure are generally required. The conductive layerclosest to a display acts to shield the interference signals.

FIG. 5 illustrates an exemplary structure which includes a display 11, ahousing 12, a driving electrode layer 13, a glass plate 14, a sensingelectrode layer 15, and an outer panel 16. In this structure the drivingelectrodes need to be boldly filled and closely arranged over the entiretouch sensor's area. During each scan, one or more driving electrodesare driven while the remaining driving electrodes are connected toground. In this case, the driving electrodes also shield theinterference signals.

FIG. 6A and FIG. 6B illustrate another structure in which drivingelectrodes 13 and sensing electrodes 15 are alternately arranged on thesame plane. In this case, the driving electrodes 13 cannot be closelyarranged to cover the sensing electrodes 15 and therefore cannot shieldthe interference signals. As such, an extra conductive shielding layer24 is required in this structure.

The above described structures have the following defects. Firstly,these structures increase the difficulties in fabricating the sensor,which may decrease product yield and increase cost. In addition, thethickness of the sensor is increased thus increasing the weight as wellas reducing the light transmittance thereof. Furthermore, onlyinterference signals from below the sensor, for example, from the LCDdisplay, can be shielded in these structures, while other interferencesignals, for example, power ripple, radio frequency, cannot beprevented.

There is currently another method of diminishing the interferences inwhich an auxiliary reference electrode is added to the sensor. It isconfigured such that this auxiliary reference electrode is onlyinfluenced by interference signals but not influenced by a touch. Assuch, the touch controller can eliminate the influence of outsideinterferences in theory by additionally sampling the referenceelectrode. However, this method would result in a complicated structureof the touch sensor and more detection ports of the touch controllerbeing occupied, which increases the cost of the system.

SUMMARY

Accordingly, the present invention is directed to a noise reductionmethod for a touch detection device which can reduce the influence ofthe external interference signals on the touch terminal's detection datawithout relying on the additional shielding layer on the sensor, thusreducing the hardware cost of the touch detection device.

In one embodiment of the noise reduction method for the touch detectiondevice, all touch detection nodes of the touch detection device aredivided into several groups (for example, with each group containing onerow, one column, or several rows or columns of detection nodes), and asynchronous sampling is performed on the touch detection nodes in eachgroup. The noise reduction method includes:

step A, performing a synchronous sampling on the touch detection nodesin one same group and storing the sampling data;

step B, comparing each sampling data against a corresponding referencedata to calculate a differential data which, as a detection data,replaces a corresponding original sampling data;

step C, calculating statistics of the detection data obtained at step Bto screen out, according to a predetermined screening condition, validdata to calculate a DC offset component indicative of a noiseingredient; and

step D, obtaining noise-filtered detection data by subtracting the DCoffset component obtained at step C from each detection data obtained atstep B.

In another embodiment, a noise reduction system for a touch detectiondevice is provided. The touch detection nodes of the touch detectiondevice are divided into one or more groups. The noise reduction systemgenerally includes a sampling unit, a differential value calculatingunit, a noise calculating unit, and a noise filtering unit. The samplingunit is used to perform a synchronous sampling on the touch detectionnodes belonging to the same group and store the sampling data. Thedifferential value calculating unit is used to compare each samplingdata against a corresponding reference data to calculate a differentialdata to replace a corresponding original sampling data. The noisecalculating unit is used to calculate statistics of the detection dataobtained by the differential value calculating unit to screen out,according to a predetermined screening condition, valid data tocalculate a DC offset component indicative of a noise ingredient. Thenoise filtering unit is used to obtain noise-filtered detection data bysubtracting the DC offset component obtained by the noise calculatingunit from each detection data obtained by the differential valuecalculating unit.

In still another embodiment, a touch terminal is provided. The touchterminal includes a touch detection device having a touch sensor unitand a touch controller unit. The touch controller unit includes thenoise reduction system as described above.

In embodiments of the noise reduction methods and system, all touchdetection nodes of the touch detection device are divided into severalgroups (for example, with each group containing one row, one column,several rows or columns of detection nodes). A synchronous sampling isperformed on the touch detection nodes in each group, such that theinfluence of the interference signals on each group of sampling data isthe same or approximately the same. By taking advantages of thecharacteristic that the influence of the interference signals on thesampling data for the same group has the same amplitude and direction,the noise ingredient in the sampling data can be filtered out as adirect current (DC) offset component, thus diminishing the influence ofthe external interference signals on the touch detection device. As oneindependent advantage, application of the noise reduction method andsystem saves the shielding layer 24 for the touch screen structure shownin FIG. 6A and FIG. 6B. Therefore, the original double-layer process issimplified to a single-layer process, thus reducing the product cost.

One or more independent aspects of the invention will become apparent byconsideration of the detailed description, claims and accompanyingdrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a typical application of a touch detection device.

FIG. 2 illustrates a matrix of touch detection sampling data.

FIG. 3 illustrates a matrix of touch detection reference data.

FIG. 4A illustrates the calculation of differential value based on thedetection sampling data of FIG. 2 and the reference data of FIG. 3.

FIG. 4B illustrates a matrix of the touch detection differential valuescalculated according to FIG. 4A.

FIG. 5 illustrates a conventional touch terminal in which the drivingelectrode layer and the sensing electrode layer are not located in thesame layer.

FIG. 6A illustrates another conventional touch terminal in which thedriving electrodes and the sensing electrodes are located in the samelayer.

FIG. 6B illustrates the shape of the driving electrode and the sensingelectrode of FIG. 6A.

FIG. 7 illustrates a logic implementation of the noise reductionprocessing for a touch detection device according to one embodiment ofthe present invention.

FIG. 8A is a flowchart of a noise reduction method for a touch detectiondevice according to one embodiment of the present invention.

FIG. 8B is a flowchart of filtering noise from detection data accordingto one embodiment of the present invention.

FIG. 8C is a 3D meshed diagram illustrating the detection data prior tonoise reduction according to one embodiment of the present invention.

FIG. 8D is a 3D meshed diagram illustrating the detection data after thenoise is reduced according to one embodiment of the present invention.

FIG. 8E is a flowchart of calculating a DC offset which is suitable fora single-point touch application according to one embodiment of thepresent invention

FIG. 8F is a flowchart of calculating a DC offset which is suitable foran application where there are a small number of touch points.

FIG. 8G is an intuitive diagram illustrating a simplified embodiment ofscreening valid data.

FIG. 8H is a histogram illustrating distribution statistics of the firstgroup of data according to one embodiment of the present invention.

FIG. 8I is a histogram illustrating distribution statistics of the fifthgroup of data according to one embodiment of the present invention.

FIG. 9 is a block diagram of a detection data noise reduction system fora touch detection device according to one embodiment of the presentinvention.

FIG. 10 illustrates a hardware structure of a touch terminal accordingto one embodiment of the present invention.

FIG. 11 is a block diagram of the noise calculating unit according to afirst embodiment of the present invention.

FIG. 12 is a block diagram of the noise calculating unit according to asecond embodiment of the present invention.

FIG. 13 is a block diagram of the noise calculating unit according to athird embodiment of the present invention.

DETAILED DESCRIPTION

Before any independent embodiments of the invention are explained indetail, it is to be understood that the invention is not limited in itsapplication to the details of construction and the arrangement ofcomponents set forth in the following description or illustrated in thefollowing drawings. The invention is capable of other independentembodiments and of being practiced or of being carried out in variousways.

In the present embodiment, the touch detection nodes are divided intoseveral groups (for example, with each group having one row, one column,several rows or several columns of detection nodes), and a synchronoussampling is performed on each group such that the sampling data for eachgroup is subject to the same or substantially the same influence of theinterference signals. By taking advantages of the characteristic thatthe influence of the interference signals on the sampling data for thesame group has the same amplitude and direction, a noise ingredient inthe sampling data can be filtered out as a direct current (DC) offsetcomponent, thus diminishing the influence of the external interferencesignals on the touch detection device.

Synchronous sampling must be performed in order to capture the uniformnoise influence in the sampling data. However, for a touch detectionsystem having a large number of touch detection nodes, it may not bepossible to synchronously sample all the detection nodes because of thelimited hardware resources or processing capability of the touchcontroller. In this regard, appropriate group sampling and processingmay be a solution to this problem. The touch detection system should beconstructed such that the spatial positions of the touch detection nodesarranged in one same group are adjacent each other. For a currentpopular capacitive multipoint touch detection device which adopts the“driving electrodes plus sensing electrodes” structure, each drivingelectrode of the touch sensor is a fundamental unit for grouping of thetouch detection nodes. As such, the synchronous sampling can easily beachieved. For touch detection devices of other structures, the detectioncircuit needs to be configured such that it is feasible to synchronouslysample the touch detection nodes arranged in one same group. If there isa small number of touch detection nodes, it is possible that there isonly one group. While the present invention is applicable to thesituation where at least two touch detection nodes are included, itshould be understood that a relatively large quantity of the touchdetection nodes contributes to a more significant noise reductionresult.

Based on the principle described above, FIG. 7 illustrates an exemplarylogic implementation of detection data noise reduction for a touchdetection device. This logic includes two layers, i.e. a sampling layerand a noise filtering layer. The sampling layer performs parallel andsynchronous sampling and operates to acquire raw sampling data of alldetection channels in one same group synchronously and rectify thesesampling data in light of a reference. The noise filtering layerstatistically analyzes each group of sampling data and filters the noiseingredient thus obtaining noise-reduced detection data.

FIG. 8A is a flowchart of an exemplary detection data noise reductionmethod for a touch detection device.

At step S801, synchronous sampling is performed on the touch detectionnodes in one same group and the sampling data are stored.

As described above, the influence of the interference signals on thetouch detection data in the same group is the same or substantially thesame. Therefore, in this embodiment, the noise component of each groupto be filtered is calculated through statistics. For example, FIG. 10illustrates a hardware structure of a touch detection device whichincludes a sensor having ten rows of sensing electrodes and fifteencolumns of driving electrodes. As illustrated, the touch detectiondevice has 10*15=150 touch detection nodes and therefore has 150sampling data:

S₁₁, S₁₂, S₁₃, …  , S₁₁₄, S₁₁₅; S₂₁, S₂₂, S₂₃, …  , S₂₁₄, S₂₁₅; …S₁₀₁, S₁₀₂, S₁₀₃, …  , S₁₀₁₄, S₁₀₁₅;

In this data matrix, S_(ij) represents the sampling data of the touchdetection nodes in the i-th row and the j-th column. For example, S214represents the sampling data of the detection node in the second row andthe fourteenth column.

The touch detection nodes are grouped according to each column ofdriving electrode, such that, the first sampling data group includes tensampling data of corresponding touch detection nodes distributed on thefirst to tenth rows of sensing electrodes and synchronously driven bythe first column of driving electrode, i.e. S₁₁, S₂₁, . . . , S₁₀₁; thesecond sampling data group includes ten sampling data of correspondingtouch detection nodes distributed on the first to tenth rows of sensingelectrodes and synchronously driven by the second column of drivingelectrode, i.e. S₁₂, S₂₂, . . . , S₁₀₂; as can be deduced by analogy,the fifteenth sampling data group includes ten sampling data ofcorresponding touch detection nodes distributed on the first to tenthrows of sensing electrodes and synchronously driven by the fifteenthcolumn of driving electrode, i.e. S₁₁₅, S₂₁₅, . . . , S₁₀₁₅.

It should be understood that the arrangement of the driving electrodesand the sensing electrodes may vary, especially in the aspect of spatialpositions, with the change in sensor layout or pin connection manner ofthe touch controller. As a result, the sampling data matrix may begrouped in different patterns in practice. However, no matter how thearrangement of the electrodes varies, the principle is that touchdetection nodes that are synchronously sampled are assigned to the samegroup, for facilitating separation and filtration of the noiseingredient from the sampling data.

At step S802, each sampling data is compared against a correspondingreference data to calculate a differential data. This differential datais used as a detection data to replace a corresponding raw samplingdata.

At this step, a subtraction is simply performed as follows:D _(ij) =S _(ij) −R _(ij)

In this subtraction, R_(ij) is a reference data corresponding to thesampling data S_(ij), and the differential data D_(ij) is thecalculation result to replace S_(ij) to thereby obtain a sampling datarectified with respect to a reference data, i.e. a detection data forfurther processing. In practice, the reference data of the touchdetection device is a sampling data under static background of no-touchand no-interference condition. The reference data is a fixed systematicerror with respect to an actual detection value of a detection node,which needs to be subtracted from a sampling data to obtain a usefuldetection data.

At step S803, statistics of the sampling data obtained throughreplacement at step S802 is calculated to screen out valid data from thesampling data according to a predetermined screening condition. Thesevalid data are used to calculate a DC offset component indicative of thenoise ingredient.

This step is a key step in the illustrated embodiment. The differentialdata obtained at step S802, i.e. the detection data, contains the touchinformation ingredient caused by a touch or approach event as well asthe noise ingredient caused by interferences. To the group of samplingdata obtained by synchronous sampling at step S801, this noiseingredient is a DC offset such that the detection data are shiftedupward or downward. The shift amplitude varies with the change in noiselevel but is fixed and systematic in one sampling. Obtaining of the DCoffset will be explained in detail in specific embodiments hereinafter.

At step S804, noise-filtered detection data are obtained by subtractingthe DC offset component obtained at step S803 from each detection datacalculated at step S802.

After performing steps S801, S802, S803 and S804 to each group ofdetection nodes within each detection period of the touch detectiondevice, it follows that the noise is removed to a large extent from thedetection data used in later processing and control by the touchdetection device, thus enabling the touch detection device to stablyoperate in an interference environment.

Step S803 is further described below in conjunction with severalembodiments.

Considering the problem to be solved by the present invention, the DCoffset component associated with one data group may be calculated usingseveral methods. A simplest one is to calculate the average of thisgroup of detection data. However, the detection data may include thelocal touch information ingredient in addition to the systematic noiseingredient, and simply calculating the average as the noise ingredientis only reasonable for those data groups without the touch informationingredient. The touch information ingredient data involving in theaverage calculation adversely affects the separation of systematic noiseingredient. In order to effectively separate the noise ingredient, it isnecessary to exclude the data having touch information ingredient fromthe calculation of the DC offset component. More specifically, it isnecessary to perform a statistical calculation such that, in principle,only valid data (i.e., those data containing as less touch informationingredient as possible) are chosen for calculation of the DC offsetcomponent. Several exemplary embodiments are given below to explain thecalculation of the DC offset component.

In a typical embodiment shown in FIG. 8B, step S803 may include thefollowing sub-steps:

-   -   step S80331, setting a threshold value to determine the validity        of a data; and setting distribution scales for statistics of        detection data;    -   step S80332, calculating the distribution statistics of a group        of detection data obtained at step S802;    -   step S80333, identifying a most concentrated data distribution        scale and a second most concentrated data distribution scale;    -   step S80334, determining whether the amplitude of an average of        the data in the most concentrated data distribution scale is        greater than the threshold value;    -   step S80335, if the determination result of step S80334 is yes,        then further determining whether the amplitude of an average of        the data in the second most concentrated data distribution scale        is less than the amplitude of average of the data in the most        concentrated data distribution scale;    -   step S80336, if the determination result of step S80335 is yes,        then storing the average of the data in the second most        concentrated data distribution scale; or    -   step S80337, if either of the determination results of step        S80334 and step S80335 is no, then storing the average of the        data in the most concentrated data distribution scale.

The average obtained at step S80336 or step S80337 is the desired DCoffset component.

The above method steps are explained below taking the example of a groupof practical sampling data for ease of understanding. For example, Table1 below shows a matrix of 150 detection data arranged in 15 groups, witheach group containing 10 detection data corresponding to 10 touchdetection nodes. Each detection data is obtained by performing asubtraction between a raw sampling data obtained under an interferenceenvironment and a corresponding reference value. FIG. 8C is itscorresponding 3D meshed diagram illustrating the detection data prior tonoise-reduction.

TABLE 1 Group Group Group Group 1 Group 2 Group 3 Group 4 Group 5 Group6 Group 7 Group 8 Group 9 Group 10 Group 11 Group 12 13 14 15 −11 64 −10−65 −46 0 53 55 6 −51 10 −63 −35 −12 36 −13 60 −9 −63 −61 −23 54 52 6−50 12 −75 −48 −9 37 −11 59 −8 −64 −85 −35 55 53 5 −48 11 −32 −85 −10 36−11 59 −10 −62 −140 −62 53 55 5 −51 12 −71 −80 −4 37 −13 61 −8 −63 −96−51 59 55 5 −51 10 −83 −85 −8 38 −16 61 −10 −64 203 47 57 49 2 −50 11 60120 −7 38 −10 61 −8 −62 268 123 52 51 3 −44 13 161 280 −6 34 −12 61 −9−62 −32 0 57 52 5 −46 13 −61 0 −8 35 −12 59 −8 −58 −61 0 51 51 6 −46 12−41 −74 −8 35 −12 56 −9 −60 −57 0 55 48 7 −50 12 −55 −93 −5 35

In this example, the detection data have a dynamic range of −512 to+511, and, a value 200 is chosen for the threshold value as a rule ofthumb (i.e., it is assumed that a detection data greater than 200 isresulted by a touch event). Distribution scales are then set accordingto Table 2, which has sixteen scales covering the values from −512 to+511.

TABLE 2 Scale Data Range −8 −449~−512 −7 −385~−448 −6 −321~−384 −5−257~−320 −4 −193~−256 −3 −129~−192 −2  −65~−128 −1  −1~−64 0  0~63 1 64~127 2 128~191 3 192~255 4 256~319 5 320~383 6 384~447 7 448~511

Step S80331 is thus accomplished. Later, at Step S80332, thedistribution statistics of the detection data obtained at Step S802 overthese scales is calculated. Exemplary calculation of the distributionstatistics is described below with respect to the first and fifth groupsof detection data in FIG. 1.

Table 3 lists the statistics result of the first and fifth groups ofdetection data of Table 1 according to the preset distribution scales ofTable 2. As shown, the ten detection data of the first group all fallwithin the scale represented by “−1”. FIG. 8H is a more intuitivehistogram illustrating the statistics result of the first group ofdetection data. The scale “−1” is the most concentrated distributionscale of the detection data as well as the second most concentrateddistribution scale, and the average of all data within this scale isless than the threshold value. Therefore, statistics of the first groupof detection data is calculated according to the following steps:

S80332→S80333→S80334→S80337

As a result, the value of the DC offset component of the first groupdetection data is −12.

FIG. 8I is a histogram illustrating distribution of the fifth group ofdetection data of Table 3 over the preset scales. As shown, the mostconcentrated distribution scale of the detection data is the scale “−1”,and the second most concentrated distribution scale of the detectiondata is the scale “−2”. Since the average of the detection data withinthe most concentrated scale is less than the threshold, statistics ofthe fifth group of detection data is calculated according to thefollowing steps:

S80332→S80333→S80334→S80337

As a result, the value of the DC offset component of the fifth group ofdetection data is −62.

Obviously, the fifth group of detection data contains substantial touchinformation ingredient. It is the aforementioned steps of processingthat guarantee an adequate separation of the noise component.

TABLE 3 Detection Detection Data Of Scales Data Of Scales Group 1(−8~+7) Group 5 (−8~+7) −11 −1 −46 −1 −13 −1 −61 −1 −11 −1 −85 −2 −11 −1−140 −3 −13 −1 −96 −2 −16 −1 203 3 −10 −1 268 4 −12 −1 −32 −1 −12 −1 −61−1 −12 −1 −57 −1

Calculating averages of the detect data of the concentrated scales forthe first to fifteenth groups results in values −12, 60, −8, −62, −62,−13, 54, 52, 5, −48, 11, −60, −71, −7, 36. These averages represent theDC offset components introduced into various groups of detection datadue to interferences, which cause the detection data to deviate more orless from reference data due to interferences rather than to touchevents. The DC offset components are subtracted from correspondinggroups of detection data thus obtaining the noise-reduced detection datalisted in Table 4 (FIG. 8D is its corresponding 3D meshed diagramillustrating the detection data after noise reduction.).

TABLE 4 Group Group Group Group 1 Group 2 Group 3 Group 4 Group 5 Group6 Group 7 Group 8 Group 9 Group 10 Group 11 Group 12 13 14 15 1 4 −2 −316 13 −1 3 1 −3 −1 −3 36 −5 0 −1 0 −1 −1 1 −10 0 0 1 −2 1 −15 23 −2 1 1−1 0 −2 −23 −22 1 1 0 0 0 28 −14 −3 0 1 −1 −2 0 −78 −49 −1 3 0 −3 1 −11−9 3 1 −1 1 0 −1 −34 −38 5 3 0 −3 −1 −23 −14 −1 2 −4 1 −2 −2 265 60 3 −3−3 −2 0 120 191 0 2 2 1 0 0 330 136 −2 −1 −2 4 2 221 351 1 −2 0 1 −1 030 13 3 0 0 2 2 −1 71 −1 −1 0 −1 0 4 1 13 −3 −1 1 2 1 19 −3 −1 −1 0 −4−1 2 5 13 1 −4 2 −2 1 5 −22 2 0

It can be reasonably concluded, from either the data of Table 4 or theintuitive 3D diagram of FIG. 8D, that the detection data havingundergone the noise reduction processing more clearly reflect the touchinformation ingredient. After the noise reduction processing of thedetection data is performed, the amplitude of the original fluctuatingbackground noise ingredient is significantly depressed. This guaranteesaccurate and stable touch detection results for later processing.

For applications where there are a small number of touch points, asimplified and practical method can be used to reduce calculation amountand increase the processing speed. As an alternative implementation ofstep S803, another simplified flowchart of calculating the DC offset isshown in FIG. 8E and illustrated in FIG. 8G. This simplified calculationis adapted for detecting a small number of touch points, for example, asingle or double-point touch situation. This embodiment includes thefollowing steps:

step S80321, setting a dividing value W for screening out valid data;

step S80322, calculating an average Avg 8G4 of the group of detectiondata obtained at step S802;

step S80323, screening out valid data from the detection data accordingto the dividing value W set at step S80321 and the average Avg 8G4obtained at step S80322 such that the detection data screened out arelocated not beyond a scope 8G1 centered at the average Avg 8G4 andhaving an amplitude of the dividing value W with respect to the averageAvg 8G4, i.e. identifying those detection data falling within theinterval between Avg−W and Avg+W as the valid data for calculating theDC offset, wherein, as a result, the data corresponding to the positions“7” and “8” that obviously contain touch information ingredient areexcluded from the data for calculating the DC offset; and

step S80324, calculating an average of the data screened out at stepS80323 to thereby obtain the desired DC offset component 8G2 (DCoffset).

As can be seen from FIG. 8G, the finally obtained valid data averageDCoffset is closer to the actual DC offset than is the aforementionedaverage Avg. In this embodiment, the dividing value W can be set as 1/16of the dynamic range of the detection data. However, in a differentapplication, the dividing value W may vary according to the data dynamicrange of the touch detection device so as to obtain a stable result.

As another simplified alternative embodiment, FIG. 8F illustratesanother flowchart of calculating the DC offset that is simplifiedrelative to that of FIG. 8B, which is adapted for detecting a smallnumber of touch points (e.g. single or double-point touch). Thisembodiment includes:

step S80311, setting distribution scales for statistics of detectiondata;

step S80312, calculating the distribution statistics of a group ofdetection data obtained at Step S802;

step S80313, identifying a most concentrated detection data distributionscale; and

step S80314, calculating an average of the data in the most concentratedscale.

The obtained average is thus the desired DC offset component.

It should be understood that all or part of the steps of the methodsdiscussed in the above embodiments may be implemented by computerprogram in combination with associated hardware. The program may bestored on a computer-readable medium such as ROM/RAM, a magnetic disc oran optical disc.

FIG. 9 is a block diagram of a detection data noise reduction system fora touch detection device according to one embodiment of the presentinvention. For ease of description, only those related to thisembodiment are illustrated in FIG. 9. This system may be integrated intoa touch terminal shown in FIG. 10. The touch terminal includes a touchdetection device having a touch sensor unit and a touch controller unitcouple to the touch sensor unit. The system of FIG. 9 may be embeddedinto touch controller unit, and the touch controller unit may beimplemented by an application specific integrated circuit (ASIC) or adigital signal processor (DSP).

Referring to FIG. 9, the detection data noise reduction system include asampling unit 91, a differential value calculating unit 92, a noisecalculating unit 93, and a noise filtering unit 94. The sampling unit 91performs a synchronous sampling on the touch detection nodes belongingto the same group and stores the sampling data. The differential valuecalculating unit 92 calculates a differential value by comparing eachsampling data obtained by the sampling unit 91 against a correspondingreference data and the differential value is used as a detection data toreplace a corresponding raw sampling data. The noise calculating unit 93then calculates statistics of the replacing detection data obtained bythe differential value calculating unit 92 to screen out, in accordancewith a preset screening condition, valid data to calculate a DC offsetcomponent indicative of a noise ingredient. Finally, the noise filteringunit 94 subtracts the DC offset component obtained by the noisecalculating unit 93 from the detection data calculated by thedifferential value calculating unit 92, thus obtaining noise-filtereddetection data.

FIG. 11 is a block diagram of a noise calculating unit 93 according to afirst embodiment of the present invention. As shown, the noisecalculating unit 93 includes a threshold and distribution scale settingmodule 9331, a detection data statistics module 9332, a first judgingmodule 9333, a second judging module 9334, and a DC offset componentdetermining module 9335. The threshold and distribution scale settingmodule 9331 is used to set a threshold value for determining thevalidity of a data and distribution scales for statistics of detectiondata. The detection data statistics module 9332 is used to calculate thedistribution statistics of a group of replacing detection data obtainedby the differential value calculating unit 92. The first judging module9333 is used to judge whether the amplitude of an average of thedetection data in a most concentrated scale is greater than thethreshold value. If the result of the judgment made by the first judgingmodule 9333 is yes, the second judging module 9334 is used to furtherjudge whether the amplitude of an average of the detection data in asecond most concentrated scale is less than the amplitude of the averageof the detection data in the most concentrated scale. The DC offsetcomponent determining module 9335 considers the average of the detectiondata in the second most concentrated scale as the DC offset component ifthe result of the judgment made by the second judging module 9334 isyes, or considers the average of the detection data in the mostconcentrated scale as the DC offset component if the result of thejudgment made by the first judging module 9333 or by the second judgingmodule 9334 is no.

FIG. 12 is a block diagram of a noise calculating unit 93 according to asecond embodiment of the present invention. The noise calculating unit93 includes a valid data dividing value setting module 9321, an averagecalculating module 9322, a valid data screening module 9323, and a DCoffset determining module 9324. The valid data dividing value settingmodule 9321 is used to set a dividing value for screening valid data.The average calculating module 9323 is used to calculate an overallaverage of the group of detection data. The valid data screening module9323 is used to screen out valid data from the detection data accordingto the dividing value set by the valid data dividing value settingmodule and the average obtained by the average calculating module 9322,such that the detection data screened out are located not beyond a scopecentered at the average and having an amplitude of the dividing valuewith respect to the average. The DC offset component determining module934 calculates an average of the detection data screened out by thevalid data screening module 9323 and this average is considered as thedesired DC offset component.

FIG. 13 is a block diagram of a noise calculating unit 93 according to athird embodiment of the present invention. The noise calculating unit 93of the third embodiment includes a distribution scale setting module9311, a distribution scale statistics module 9312 and a DC offsetcomponent determining module 9313. The distribution scale setting module9311 is used to set distribution scales for statistics of detectiondata. The distribution scale statistics module 9312 calculatesdistribution statistics of the group of replacing detection dataobtained by the differential value calculating unit. The DC offsetcomponent determining module 9313 calculates an average of the detectiondata in a most concentrated scale obtained by the distribution scalestatistics module 9312 and this average is considered as the desired DCoffset component.

In another embodiment, a touch terminal is provided which includes atouch detection device. The touch detection device includes a touchsensor unit and a touch controller unit coupled to the touch sensorunit. The touch controller unit includes a touch detection data noisereduction system as described in the foregoing embodiments.

This system is configured and operates in the same way as discussed inthe foregoing embodiments and, therefore, explanation thereof is notrepeated herein. This embodiment is suitable for various types of touchdetection devices.

While there has been described in the foregoing description preferredembodiments of the present invention, it will be understood by thoseskilled in the art that many variations or modifications in details ofdesign or construction may be made without departing from the scope ofthe present invention.

What is claimed is:
 1. A noise reduction method for a touch detectiondevice, wherein touch detection nodes of the touch detection device aredivided into one or more groups and the noise reduction methodcomprises: step A, performing a synchronous sampling on the touchdetection nodes in one same group and storing the sampling data; step B,comparing each sampling data against a corresponding reference data tocalculate a differential data which, as a detection data, replaces acorresponding original sampling data; step C41, setting a plurality ofmutually exclusive data ranges each having a preset upper limit and apreset lower limit; step C42, comparing each detection data of a groupof detection data obtained at step B with the preset upper limit and thepreset lower limit of each of the plurality of mutually exclusive dataranges to determine which data range each detection data of the group ofdetection data falls in; step C43, calculating the number of detectiondata in each data range to identify a most concentrated data range inwhich the number of the detection data fall is greatest; and step C44,calculating an average of all the detection data in the mostconcentrated data range, the obtained average being considered as a DCoffset component; and step D, obtaining noise-filtered detection data bysubtracting the DC offset component obtained at step C44 from eachdetection data obtained at step B.